mlsanityData to 7 Oct 2026

Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries

arXiv 2409.15645 ↗First posted 24 Sep 2024quant-ph stat.MLcited by 3

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Abstract (arXiv)

The nexus of quantum computing and machine learning - quantum machine learning - offers the potential for significant advancements in chemistry. This review specifically explores the potential of quantum neural networks on gate-based quantum computers within the context of drug discovery. We discuss the theoretical foundations of quantum machine learning, including data encoding, variational quantum circuits, and hybrid quantum-classical approaches. Applications to drug discovery are highlighted, including molecular property prediction and molecular generation. We provide a balanced perspective, emphasizing both the potential benefits and the challenges that must be addressed.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 17 of its 100 references that are in the map. First posted on arXiv 24 Sep 2024.

Builds on

17 of 100 references.

References · 17

  1. 2020Variational Quantum Algorithmscited by 687
  2. 2016Quantum Machine Learningcited by 325
  3. 2021Generalization in quantum machine learning from few training datacited by 214
  4. 2022Graph neural networks for materials science and chemistrycited by 181
  5. 2019Mol-CycleGAN - a generative model for molecular optimizationcited by 66
  6. 2022Quantum Vision Transformerscited by 48
  7. 2021Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstructioncited by 20
  8. 2017Quantum autoencoders via quantum adders with genetic algorithmscited by 19
  9. 2018Experimental Implementation of a Quantum Autoencoder via Quantum Adderscited by 12
  10. 2024DirectMultiStep: Direct Route Generation for Multistep Retrosynthesiscited by 11
  11. 2022Quantum activation functions for quantum neural networkscited by 10
  12. 2023ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generationcited by 8
5 more
  1. 2022HAC-Net: A Hybrid Attention-Based Convolutional Neural Network for Highly Accurate Protein-Ligand Binding Affinity Predictioncited by 6
  2. 2023Quantum Convolutional Neural Networks for Multi-Channel Supervised Learningcited by 4
  3. 2021Convolutional Neural Nets in Chemical Engineering: Foundations, Computations, and Applicationscited by 3
  4. 2021Prime Factorization Using Quantum Variational Imaginary Time Evolutioncited by 2
  5. 2023Kernel-Elastic Autoencoder for Molecular Designcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025Layerwise Federated Learning for Heterogeneous Quantum Clients using Quoruscited by 4
  2. 2026Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learningcited by 1
  3. 2026An Efficient Quantum Circuit for Flow Model Execution Using Quantum Neural Networkscited by 0